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Artificial Intelligence with Python

Artificial Intelligence with Python

By : Prateek Joshi
3.6 (34)
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Artificial Intelligence with Python

Artificial Intelligence with Python

3.6 (34)
By: Prateek Joshi

Overview of this book

Artificial Intelligence is becoming increasingly relevant in the modern world. By harnessing the power of algorithms, you can create apps which intelligently interact with the world around you, building intelligent recommender systems, automatic speech recognition systems and more. Starting with AI basics you'll move on to learn how to develop building blocks using data mining techniques. Discover how to make informed decisions about which algorithms to use, and how to apply them to real-world scenarios. This practical book covers a range of topics including predictive analytics and deep learning.
Table of Contents (17 chapters)
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Chapter 3. Predictive Analytics with Ensemble Learning

In this chapter, we are going to learn about Ensemble Learning and how to use it for predictive analytics. By the end of this chapter, you will know these topics:

  • Building learning models with Ensemble Learning
  • What are Decision Trees and how to build a Decision Trees classifier
  • What are Random Forests and Extremely Random Forests, and how to build classifiers based on them
  • Estimating the confidence measure of the predictions
  • Dealing with class imbalance
  • Finding optimal training parameters using grid search
  • Computing relative feature importance
  • Predicting traffic using Extremely Random Forests regressor
CONTINUE READING
83
Tech Concepts
36
Programming languages
73
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Artificial Intelligence with Python
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